Datasets & Competitions
Dynamic models are indispensable for the optimization, prediction and control of thermal comfort in buildings.A new method is proposed for modeling the nonlinear dynamics of radiator-heated buildings and measuring modeluncertainties. The model uncertainty range obtained by the method can describe the uncertainties in the presence of model structure deviations and unknown noise distributions, without making restrictive assumptions that the noise follows a Gaussian distribution as in existing methods.
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Schematic diagram to illustrate the separation and identification of nonlinear flow characteristics for the proposed method. Due to a fact that steam turbines and generators have different dynamic characteristics at different operating points, the static nonlinear flow characteristic (e.g., yellow solid lines in (a)) is overwhelmed by input and output data with dynamic characteristics, such as the blue dots in (a) and their corresponding time series are shown in (b). The key to identifying the nonlinear flow characteristic is to separate it from the linear dynamic submodels at different ope
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This is a data set of identification for nonlinear flow characteristics of paper ''Identification for nonlinear flow characteristics of main steam regulating valves by mining special segments from industrial big data ''.
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